Photogrammetry-based bending monitoring and load identification of steel truss structures

Abstract

The bending of steel truss structures is an important gauge for detecting, identifying, and evaluating potential issues with structural safety performance. The limitations and high cost of traditional monitoring methods make it challenging to carry out stable long-term monitoring. Therefore, this paper developed a displacement monitoring system for steel truss structures which fulfill the requirements of having low cost, high stability, and ease of operation. The system is based on the improved sub-pixel positioning technology, achieving precise positioning in unfavorable conditions such as long structure-camera distance, angle skew, and dim light. Then, this system was calibrated through field experiment and compared with other measurement systems. Finally, a load identification method was developed to identify discrepancies between the true load and the design load. This method uses optimization functions to identify the true load applied in the experiment, and the optimization parameter obtained by a genetic algorithm iteration is output as the optimal solution. The results suggest that the photogrammetric system performs well in practical engineering applications and can provide advantages including high precision, low cost, simple operation, etc. Results obtained by the load identification method agree well with measurements obtained from the actual structure, and can serve as a tool for evaluating the mechanical properties of similar structures. This method monitors potential risks of steel truss structures, and greatly improve the stability and safety of such structures.